Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.250118v1?rss=1 Authors: Nishizaki, S. S., Boyle, A. P. Abstract: Motivation: Aberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly associated with human disease. However, the majority of methylation-sensitive positions within transcription factor binding sites remain unknown. Here we introduce SEMplMe, a computational tool to generate predictions of the effect of methylation on transcription factor binding strength in every position within a transcription factors motif. Results: SEMplMe uses ChIP-seq and whole genome bisulfite sequencing to predict effects of methylation within binding sites. SEMplMe validates known methylation sensitive and insensitive positions within a binding motif, identifies cell type specific transcription factor binding driven by methylation, and outperforms SELEX-based predictions. These predictions can be used to identify aberrant sites of DNA methylation contributing to human disease. Availability and Implementation: SEMplMe is available from https://github.com/Boyle-Lab/SEMplMe. Copy rights belong to original authors. Visit the link for more info